Parallel Scaling Law for Language Models
Paper
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2505.10475
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Published
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83
Paradigm
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Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective
Paper • 2505.15045 • Published • 54 -
Scaling Diffusion Transformers Efficiently via μP
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Vision Transformers Don't Need Trained Registers
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MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
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Marrying Autoregressive Transformer and Diffusion with Multi-Reference Autoregression
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